Currently, convergence factors for ANC are determined by experimentation. ANC systems are based on adaptive filter technology. The adaptive filter algorithm normally used for ANC is gradient search Least Mean Squared (LMS). A key point to the stability of an LMS system is the choice of the convergence factor (or step size μ). For an automotive application, the engine hum or boom is cancelled with an ANC system. Since the engine boom changes frequency as the engine Revolutions per Minute (RPM) changes, a unique convergence factor must be considered for each discrete frequency allowed in the ANC system. For an ANC system with M microphones and K speakers, the number of unique frequency responses required is M*K. If the ANC system has an operating frequency range of 20-250 Hz, there are 230 unique frequencies with a frequency resolution of 1 Hz. This could require 230*K unique convergence factors. These convergence factors are currently determined by experimentation. The task of creating tables of convergence factors for an ANC Systems becomes very costly and time consuming.
While many advances have been made to improve automotive ANC algorithms, each method has its own set of problems. Each method has to be custom tuned for each targeted enclosure. A large part of this tuning is coming up with stable values for μ. If there were only one value this would not be an issue. Given the specifications for a typical ANC system:                two microphones        three speakers        Frequency range of 20-250 Hz        Frequency resolution of 1 Hz.There would need to be 230*3=690 values for μ. If the average time to calibrate/re-calibrate each value of μ is twenty minutes with two technicians, then the total man-hours required for tuning would be 460 hours. Many of these hours are spent in a car on a dynamometer rack, and there are additional costs associated with using a dynamometer.        